The present invention relates to image processing, compressing, decompressing, transmitting, sending and receiving devices and methods, programs thereof and a displaying device, and more particularly to an image processing device, an image compressing device, an image decompressing device, an image transmitting device, an image sending device, an image receiving device, a displaying device, an image processing method, an image compressing method, an image decompressing method, an image transmitting method, an image sending method, an image receiving method and programs thereof for use in achieving high image quality, largely improving image quality and largely improving or removing granular quality deterioration in image compression and decompression processing in conformity to memory capacity of a display having a memory for storing a raster image, and improving efficiency for transmitting the raster image from a computer to the display.
At present, a method for transmitting raster images together with their frame frequencies is used as an image transmission method from a computer to a display. In this method, image data is not compressed and a data transmission amount becomes large.
Moreover, recently one screen of raster images is stored in memory not only at a computer side but also at a display side.
In this case, the image data is not compressed and the memory capacity becomes large. To produce images with higher definition and more gradations, the data transmission amount and the memory capacity increase and technical difficulties and costs further enlarge.
In the case of a superimposed image displaying, for instance, overlaying a screen image on another screen image, plural screen images such as images and characters must be prepared as input images to increase the data capacity of the input images. As a result, it becomes difficult to store the input images into a memory and to transmit their image data via a path having a limited bus width.
Furthermore, in a display of a mobile terminal or the like, having a low maximum resolution of its surface screen, when a large image such as a map or the like is displayed, scrolling is required. Although this scrolling display is a simple operation at first glance, the image data is frequently rewritten in a display memory with the result that its power consumption increases.
In order to meet not only the high definition and the multiple gradations of images without increasing the data transmission amount and the memory capacity but also multi-functions such as the image superimposition and the image scrolling, the images may be compressed in a file type such as JPEG (Joint Photographic Experts Group) or GIF (Graphics Interchange Format) to transmit the compressed image files.
However, since compression and decompression processing at every frame requires a high-speed processor, cost increases. Further, image quality varies considerably with features of images and it is difficult to obtain the same level of image quality for all images.
Another method for compressing image data called a BTC (Block Truncation Coding) capable of performing an operation relatively simpler than the aforementioned method has been developed. In the BTC, image data is divided into square blocks with a predetermined number of pixels and average value data for each block is calculated in the same bit number as the original image data. A difference between gradation data and the average value data for each pixel is calculated, and quantized difference data and the average value data are held.
In the related art, an image data compression by the BTC is disclosed in Japanese Patent Application Laid-Open No. Hei 10-66072, “Image Coding Device and Image Coding-Decoding Method” (Patent Document 1).
However, in an image data compression and decompression by the BTC, the average value data is different at every block and the difference data is quantized. Hence, a block noise occurs at the boundary between blocks to cause a false outline. When gradation values of pixels within a block are largely dispersed (a difference between the minimum and maximum gradation values within the block is large), a compression rate of the difference data at the quantization goes up and image deterioration increases. In this method, the image quality varies depending on the features of the images as well and it is difficult to obtain the same level of image quality for all images.
In this case, when blocks are small, the effect of the compression can be hardly obtained and a circuit designed for a certain size of block is required, which increases a circuit scale.
This is because line memory for holding the pixel data is needed since pixel data within a block extending to the sub-scanning direction must be processed in a batch when this method is applied to a display. A raster image is one-dimensional data and when a block is extending to the sub-scanning direction, the image data must be held until the next line of the image data is input after a preceding line was input.
That is, in the image data compression and decompression by the BTC, although the image compression is carried out to reduce the memory capacity, line memory is required to weaken the effect of the memory capacity reduction. As described above, larger blocks are preferable to heighten the effect of data compression. However, larger the blocks are, the more line memory is required (if the image data is not stored in the line memory until all the pixel data within the block is obtained, the processing cannot be executed). This problem becomes further noticeable.
As described above, the image quality largely varies depending on the features of images in these conventional methods. In order to reduce the variation of image quality, a reduction of a bit plane number of a raster image can be considered. A bit plane number represents a bit number n of data that expresses gradations of a digital image quantized in 2n gradations. A plurality of methods for reducing the bit plane number such as a multi-valued dither method, a fixed threshold value method, and the like are disclosed in “Image Electronics Handbook”, 1993, Corona Publishing Co., Ltd. (Nonpatent Document 1).
In the multi-valued dither method or fixed threshold value method, different from the image compression method using JPEG files, GIF files or the BTC, there is no need to decompress the compressed images.
However, in the conventional multi-valued dither method or fixed threshold value method, the bit plane number reduction causes a false outline, false colors and a grainy feeling or granular quality deterioration such as low (coarse) granular quality of the image to deteriorate the image quality.
In order to solve these problems, a conventional image processing system has been proposed as disclosed in Japanese Patent Application Laid-Open No. 2003-162272, “Image Processing Device, Image Transmission Device, Image Receiving Device and Image Processing Method” (Patent Document 2). FIG. 1 shows an image processing device disclosed in Patent Document 2. In this case, a dither processing is applied to an input image based on its XY coordinates and the processed image is quantized to store the obtained image data into a memory. The image data read out of the memory is inversely quantized and the same dither matrix as used in the dither processing of the input image is added to the image data to send the resulted image data to a display.
In the processing of Patent Document 2, image quality is steadily obtained for any images. Moreover, a circuit scale enlarged by applying the processing of Patent Document 2 to the image is smaller than a reduced scale of a circuit having a memory capacity obtained by compressing a relatively small image, and hence this processing can be also applied to a mobile phone as a frame memory capacity reduction method.
However, in the conventional system disclosed in Patent Document 2, the granular quality deterioration in the image can be slightly observed. In particular, the low granular quality is conspicuous in a mild gradation image (a gradation change is mild or small in a certain area of the image) and a plain gradation image (gradation is fixed in a certain area).